Studies and Scientific Researches. Economics Edition, No 34, 2021 http://sceco.ub.ro 36 KEY DRIVERS OF BRAND LOYALTY AMONG HOMOGENOUS FIRMS: THE CASE OF THE NIGERIAN TELECOMMUNICATION INDUSTRY Obukohwo Oba Efayena Foundation for Economic Research and Training (FERT) Lagos, Nigeria. economix4life@gmail.com Enoh Hilda Olele Department of Economics Delta State University, Nigeria. oleleehilda@gmail.com Ngozi Patricia Buzugbe Department of Arts & Humanities Delta State Polytechnic, Ogwashi-Uku, Delta State, Nigeria buzugbengozi@gmail.com Abstract No firm operate in a vacuum without interacting within the immediate environment as well as reacting and counteracting with internal and external forces. Each firm operating in an industry strive to expand its operations gaining more market shares, while warding off rival firms from gaining competitive grounds comparatively. The Nigerian telecommunication industry possesses the characteristics of an oligopolistic industry which is predominantly a competitive industry with rival firms vying to retain customers’ loyalty and expand market share. The study thus investigates the impact of key drivers on brand loyalty among the firms. The PLS-SEM analysis employed in the study showed that while communication, cooperation and trust positively impact brand loyalty, product quality, value-for-money and service quality had no significant impact on brand loyalty. The study thus recommend that individual firms take conscientious efforts to develop and implement policies to stimulate brand loyalty as well as expand market share. The policy implications of this study can be applied to other competitive industries in Nigeria. Keywords brand loyalty; firms; telecommunication; product quality; competitive JEL classification L80; M21 1. Introduction With advancing technologies, the global telecommunication industry is becoming more digitalized and competitive. This industry has created a solid framework for a global digitalized economy, and has connected all echelons of social and economic activities. The importance of the telecommunication industry cannot be overemphasized. Even in period of the global health crisis such as the ravaging Covid-19 pandemic, the industry powered economic activities the world over, averting a potential “total lockdown” crisis. Apps such as Zoom, Cisco Webex, WhatsApp, Skype, Viber, Wechat, Line, You Tube and others were all powered by data from the telecommunication industry. The narrative is not different in Nigeria as the industry has evolved through the years and have been striving to meet the demand of the teeming populace. With general inefficiency in the country’s indigenous communication firm, Nigeria Telecommunication Limited (NITEL) which necessitated full and partial liberalization Efayena, Olele, Buzugbe 37 of the industry in 1992 and 1999 respectively, more homogenous firms have evolved to meet up with the challenges of telecommunication in Nigeria. Specifically, there are about eight licensed telecommunication firms in Nigeria which include MTN, Airtel Nigeria, Globacom, 9Mobile, Smile, Ntel, Swift Network, Spectranet and Mainone with the first four having a larger share of the market. The metamorphosis in the Nigerian telecommunications industry has resulted in the migration from traditional landlines to various brands of handheld phones. The teledensity, landline telephones per 100 individuals domiciled in a given area, has generally been on a downward trajectory in recent years. Clearly, this trend showed that users are gradually moving from the use of landline telephones to more sophisticated phones. This also implies that service providers such as 9MOBILE, AIRTEL, GLO and MTN have taken over a large share of the previously monopolistic telecommunication industry and has more or less formed an oligopolistic market structure following government’s full and partial liberalization of the industry in 1992 and 1999 respectively. This trend has resulted in greater competition since customers have a basket of alternatives from which choices can be made hence network upgrade and expansion of service portfolios is the focus of network providers in order to retain customers, while trying to attract new ones to their organizations. The automate goal of rival firms in the Nigerian telecommunication industry is to become a customer-centric firm. Competition among rival firms is a pervasive phenomenon. In general, as competition between firms intensifies, the need to retain customers comes to the fore. This is important since brand loyalty will impact the profitability of firm (Climes, 2016; Faroog, 2018). Such loyalty on the part of the customers has to do with the attitude and behaviour of the customers, with customers willing to persist to the product(s) irrespective of choice alternatives (Cossio-Silva, et al., 2016; Lian & Yoong, 2017). This has resulted in cost reduction and market attraction (Dean, 2007; Yang, et al., 2019; Somasundaram, et al., 2018; Ali, et al., 2019; Budianto, 2019). There are several studies on the positive effect of brand loyalty on organizational performance. Such studies range from the banking sector (Bogati & Vongurai, 2016; Tweneboah & Farley, 2015); the airline industry (Azad & Sadeghifar, 2019; Lin, et al., 2018); the hospitality industry (Cheng, et al., 2019; Aldaihani & Ali, 2018; Chang, 2013; Chien-Hsiung, 2011; Habib, et al., 2011); the telecommunication industry (Husain, 2015); the textile industry (Yeap, et al., 2018); the electrical industry (Leong & Rahman, 2019); to the automobile industry (Loureim, et al., 2017); among others. In Nigeria, brand loyalty persists in several industries. For instance, it can be seen in the Nigerian carbonated soft drinks market, which is predominantly dominated by Coca-Cola and Pepsi for many decades. Although, Coca-Cola has been operating in Nigeria since, 1951, it can clearly be observed that brand loyalty exists when the volume of consumption of Pepsi drinks which only came into operation in Nigeria during the early 1990s is considered. Individuals exhibit long-standing loyalties to these brands as the Coca-Cola and PepsiCo adapt several aggressive strategies to retain customers as well as expand market share. Further, brand loyalty can also been seen among mobile phones brands. This market is predominantly occupied with brands such as NOKIA, TECHNO, ITEL, Blackberry, among others. As competitive as it is, the issue of brand loyalty in the Nigerian telecommunication industry is oblivious to many. Drawing from the fierce competition among rival firms and the volatile demand of their products, the Nigerian telecommunication industry requires an in-depth study as to brand loyalty since this holds the key to firms’ profitability and sustainability in the industry. Explicitly, there is urgent need to appraise the impact of variables such as product quality, trust, cooperation, communication and commitment on brand loyalty. This is essential since the general performance and sustainability of the firms depend on retain customers’ loyalty and KEY DRIVERS OF BRAND LOYALTY AMONG HOMOGENOUS FIRMS: THE CASE OF THE NIGERIAN TELECOMMUNICATION INDUSTRY 38 market expansion. This study is thus geared at evaluating the impact of brand loyalty in the Nigerian telecommunication industry. Following this brief introduction, Section 2 presents the methods employed in the study, sections 3 and 4 discusses the results of the study and concludes the study, respectively. 2. Methods 2.1. Sampling Technique The study adopted a cross-sectional approach in collecting data from customers of the four (4) giant telecommunication firms in Nigeria, namely, 9MOBILE, AIRTEL, GLO and MTN. Obtaining the entire population of customers of these firms is impossible given space and time. The population of telecommunication services exceeds 1,000,000 individuals. According to Gill, et al. (2010), within a 95 percent confidence level, a minimum of 384 individuals are adequate for such a study. This study distributed a total number of 500 questionnaires which far exceeds the given threshold. Therefore, a simple random sampling technique was adopted in which every individual in the population has equal rate of being included in the sample, thus avoiding sampling bias. Visits were made to the service centres of the various telecommunication operators to elicit the needed information. Due to restrictions brought about by the Covid-19 pandemic, visitations were made within three months after the removal of vehicular and human movements to ensure that a relatively large proportion of end-users were captured in the study. This time period is deemed appropriate since it will adequately reflect customers’ loyalty to the brands after the complete lockdown of economic activities. Collection of questions spanned over three (3) months with a total of 467 questionnaires returned. After appropriate consideration, only 431 questionnaires were suitable for analysis. 2.2. Data A self-administered questionnaire was employed for the study. The questionnaire consists of two sections. Section A elicits respondents’ bio and socioeconomic information, while Section B covers the relational variables related to brand loyalty. The choice of variables employed in the study followed previous studies (Leong & Rahman, 2019; Yeap, et al., 2018). The variables include brand loyalty, product quality, cooperation, communication, trust, value-for-money and service quality. These variables all have three (3) measurement items. While the brand loyalty was measured using a 5-point Likert scale (1 = definitely disagree, 2 = disagree, 3= neutral, 4 = agree, 5 = definitely agree) the other variables was measured with a 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). The internal reliability was obtained from a pilot run and the Cronbach alpha coefficients for brand loyalty, product quality, cooperation, communication, trust, value-for-money and service quality were estimated at 0.69, 0.81, 0.78, 0.84, 0.83, 0.67 and 0.71, respectively. These estimates were above the 0.60 minimum alpha (Nunnally, 1978). 2.3. Method of Data Analysis The study adopted the partial least squares structural modelling (PL-SEM) technique. The convergent validity and the discriminant validity was carried out to ensure the reliability of the empirical results. The findings of this study can therefore be applied to other industries in Nigeria. Efayena, Olele, Buzugbe 39 3. Results 3.1. Descriptive Statistics An x-ray of the collected results showed that a large proportion of the respondents (69.8 percent) were females. Most of the respondents were within the 30-45 age bracket (59.3 percent), while the least was within the 60+ age bracket (2.1 percent). Education-wise, most of the respondents had university first degrees (47.3 percent). 8.2 percent of the respondents had no formal education, while the educational class with the least respondents was postgraduate degree (2.9 percent). 3.2. Empirical Findings 3.2.1. Principle Factor Test In order to avoid the common method bias in which the measurement method rather than the constructs determines the variance in the variables employed, the study employed the Harman’s single factor test. The principle factor obtained was 29.13 percent. This was below the proposed threshold (Podsakoff & Organ, 1986). This indicated that the model was devoid of common method bias. 3.2.2. Measurement Model The PLS-SEM analysis results were presented in Table 1. It presented the composite reliability scores and average variance extracted (AVE) for all the constructs in the model. Table 1. Convergent validity Construct Measurement Item Indicator Reliability Average Variance Extracted (AVE) Composite Reliability Brand Loyalty (BL) BL1 0.811 0.763 0.921 BL2 0.937 BL3 0.803 Product quality (PQ) PQ1 0.822 0.831 0.909 PQ2 0.907 PQ3 0.926 Cooperation (CN) CN1 0.930 0.806 0.938 CN2 0.863 CN3 0.871 Communication (CM) CM1 0.842 0.716 0.873 CM2 0.819 CM3 0.837 Trust (TT) TT1 0.843 0.762 0.916 TT2 0.804 TT3 0.897 Value-for-money (VM) VM1 0.853 0.765 0.911 VM2 0.910 VM3 0.887 Service quality (SQ) SQ1 0.941 0.827 0.951 SQ2 0.916 SQ3 0.902 Source: Authors’ compilation KEY DRIVERS OF BRAND LOYALTY AMONG HOMOGENOUS FIRMS: THE CASE OF THE NIGERIAN TELECOMMUNICATION INDUSTRY 40 A cursory observation of Table 1 shows that the coefficients of the indicator reliability of all the constructs were above 0.80, with a lower bound of 0.803 and an upper bound of 0.941. The lower bound of the composite reliability was 0.873, while the upper bound was 0.951. These values exceeded the 0.70 threshold value (Hair, et al., 2017). The same was true of the average variance extracted (AVE) values obtained. Each of these values exceeded the 0.50 threshold value (Fornell & Larcker, 1981). The results of the convergent validity showed that the variance in the variables was largely explained by their constructs. There was also a need to establish that a given construct was truly distinct from other constructs in the model. The study employed the Heterotrait-Monotrait Ratio of Correlation (HTMT) test. Table 2 presents the results of the discriminant validity test. Table 2. Discriminant validity Construct BL PQ CN CM TT VM SQ BL 0.734 PQ 0.411 0.717 CN 0.420 0.379 0.749 CM 0.327 0.368 0.417 0.715 TT 0.501 0.429 0.476 0.413 0.759 VM 0.336 0.437 0.346 0.532 0.551 0.723 SQ 0.419 0.528 0.438 0.391 0.332 0.468 0.724 Source: Authors’ compilation The values in Table 2 showed the correlations between the constructs in the model. Henseler, et al. (2019) proposed an HTMT criterion of 0.85. The correlation values showed that the constructs are distinctly different and unique since the values were below the proposed threshold of 0.85. That implied that each construct can be judged on its own merit. 3.2.3. Structural Model The structural econometric model results in more than the conventional causal relationships in their reduced form. A well specified structural model is capable of identifying the mechanisms which determine outcomes, as well as quantify impacts on specific outcomes (Hamish & Meghir, 2017). Thus, the structural model was highly recommended for the study since the structural model has the capacity of determining the impact of each of the key drivers of brand loyalty. By applying a bootstrapping procedure with 4,999 resampling following Leong and Rahman (2019), the study obtained the following results as presented in Table 3. Table 3. Empirical Results Relationship Beta t-statistics p-value Decision H1: PQ BL 0.263 0.199 0.438 Not supported H2: CN BL 0.158** 4.211 0.000 Supported H3: CM BL 0.259** 3.966 0.000 Supported H4: TT BL 0.183** 4.602 0.000 Supported H5: VM BL 0.326 0.187 0.513 Not supported H6: SQ BL 0.116 0.355 0.214 Not supported Note: * and ** signify p < 0.05 and p < 0.01 significance level, respectively. Source: Authors’ compilation Efayena, Olele, Buzugbe 41 Of the explanatory variables, cooperation (β = 0.158, p < 0.01), communication (β = 0.0.259, p < 0.01) and trust (β = 0.183, p < 0.01) have a significant and positive impact on the dependent variable (brand loyalty). Thus, only H2, H3 and H4 were supported. However, product quality, value-for-money and service quality did not exert any significant impact on brand loyalty. Hence, H1, H5 and H6 were not supported. These findings contrasted previous studies (Grace & O’Cass, 2005; Krystallis & Chrysochuo, 2014). The predictive accuracy of the model captured by the coefficient of determination (R2) was high. An estimated R2 of 0.632 shows that the model adequately explained variance in brand quality. 4. Concluding Remarks The study analyzed the impact of selected relational variables on brand loyalty among homogenous firms in the Nigerian telecommunication industry. Basically, cooperation, communication and trust exerted a significant and positive impact on brand loyalty, while impact of product quality, value-for-money and service quality on brand loyalty was insignificant. The study found that in order to achieve individual firm’s objectives of loyalty, retention and market expansion, as well as careful consideration should be given to policies that enhance the quality of the firm’s products and services. This will ensure that customers maximize their value-for-money. 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